DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Drawings
The applicant’s drawings submitted are acceptable for examination purposes.
Response to Arguments
Applicant’s arguments with respect to claim(s) 13-24 have been considered but are moot because the new ground of rejection does not rely on the same references applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Please see rejections in the present Office action below.
In response to the applicant's argument that "Prior to entry of the amendments presented herein, claims 13-32 were pending in this application. Claims 13-32 stand rejected for the reasons set forth below. Claims 13 and 15 are amended. Claims 25-32 are cancelled," the Examiner traverses. Claim 15 was not amended in the claims filed 30 December 2025, for Claim 15 remains previously presented. However, Claim 19 has been amended in the present application.
Claim Rejections - 35 USC § 112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 13-24 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
With respect to Claim 13, the limitations “a boundary of a vessel with a vessel diameter greater than a pre-set vessel diameter" and "a small vessel annotation result formed by annotating a direction of a vessel not greater than the pre-set vessel diameter” have relative terms which render the claim indefinite. The phrases “vessel diameter greater than a pre-set vessel diameter" and "a small vessel annotation result” are not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention.
These limitations are indefinite because the pre-set vessel diameter is not defined, nor is it recited who or what sets it, how it is determined, or under what conditions, and thus, leaves the threshold arbitrary and variable. It is also unclear since the limitations utilize relative comparison (e.g., “greater than,” “not greater than,” “a small vessel,” etc.) without specifying what the vessel direction refers to, how it is measured, or how it relates to vessel diameter. The pre-set value, measurement methodology, diameter boundaries, and evaluation conditions are also not defined, for there is no way to determine how small the annotation result must be or how much greater the vessel boundary must be relative to the pre-set diameter. Thus, a person having ordinary skill in the art cannot objectively determine which vessels qualify, how annotations are formed, or where the claim boundary lies. Since the scope cannot be ascertained, the claims are indefinite under § 112(b). Furthermore, the arteriovenous vessel annotation results, artery annotation result, vein annotation result, boundary of a vessel, vessel diameter, a direction of a vessel, loss function, and a weight of a region being adjusted are also rendered indefinite by the use of the terms “pre-set vessel diameter” and “small vessel annotation result.”
For the prosecution on merits, examiner interprets the claimed subject matter described above as introducing optional elements, optional structural limitations, optional expressions, and optional functionality within a method for measuring lesion features of hypertensive retinopathy.
Applicant should clarify the claim limitations as appropriate. Care should be taken during revision of the description and of any statements of problem or advantage, not to add subject-matter which extends beyond the content of the application (specification) as originally filed.
If the language of a claim, considered as a whole in light of the specification and given its broadest reasonable interpretation, is such that a person of ordinary skill in the relevant art would read it with more than one reasonable interpretation, then a rejection of the claims under 35 U.S.C. 112, second paragraph, is appropriate. See MPEP 2173.05(a), MPEP 2143.03(I), and MPEP 2173.06.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 13-24 are rejected under 35 U.S.C. 103 as being unpatentable over Jin et al. CN 111681276 A (see machine translation; herein after "Jin") in view of Badawi SA, Fraz MM. Multiloss Function Based Deep Convolutional Neural Network for Segmentation of Retinal Vasculature into Arterioles and Venules, Biomed Res Int. 2019 Apr 14; pgs. 1-17 (herein after "Badawi").
With respect to Claim 13, Jin discloses a method for measuring lesion features of hypertensive retinopathy (method for determining the diameter of arteries and veins in a fundus image; [0045]), comprising: acquiring a fundus image ([0122]);
identifying an optic disc region of the fundus image ([0123-124]) and dividing the fundus image into at least three regions comprising a first region (center of the position of the optic disc; [0064]), a second region (first distance; [0064]), and a third region (second distance; [0064]) based on the optic disc region [0123-124];
performing artery and vein segmentation (artery and vein determination unit 440; [0125]) on the fundus image by a deep learning-based (deep neural network model; [0055]) arteriovenous segmentation model (through artery and vein determination unit 440, determines the arteries and veins that meet the preset conditions according to the blood vessel segmentation image in the annular area; [0125]) wherein the arteriovenous segmentation model ([0125]) is trained by a training fundus image (preprocessed fundus image; [0053]) and an arteriovenous vessel annotation result (blood vessels in the fundus image to be detected can be directly segmented based on the deep neural network model, and blood vessel
segmentation image; [0055]) of the training fundus image (preprocessed fundus image; [0053]), and
measuring the lesion features of the hypertensive retinopathy in the fundus image (diameter ratio determination unit 450; [0126]) based on the three regions and the arteriovenous segmentation results (annular region, center of the position of the optic disc, first distance, and second distance; [0064]), the lesion features comprising at least one of arteriovenous cross-indentation features, arteriolar local stenosis features, and arteriolar general stenosis features (narrowing the recognition range, which not only reduces the computational complexity but also increases the accuracy; [0010]).
Jin does not appear to explicitly teach the following limitations wherein the arteriovenous segmentation model is configured to segment an artery and vein in the fundus image to directly acquire an arteriovenous segmentation result, wherein the arteriovenous segmentation results comprise an artery segmentation result and a vein segmentation result, and the arteriovenous vessel annotation result of the training fundus image, the arteriovenous vessel annotation results comprising an artery annotation result and a vein annotation result formed by annotating a boundary of a vessel with a vessel diameter greater than a pre-set vessel diameter in the training fundus image and a small vessel annotation result formed by annotating a direction of a vessel not greater than the pre-set vessel diameter, when a loss function is calculated, a weight of a region corresponding to the small vessel annotation result is adjusted based on the small vessel annotation result.
However, in the same field of endeavor, Badawi teaches a multiloss function based deep convolutional neural network for segmentation of retinal vasculature into arterioles and venules (pg. 1), wherein a deep learning-based (deep encoder-decoder designed based on entire convolutional neural system design, optimized deep learning architecture; pg. 3, col. 2, para. 2) arteriovenous segmentation model (semantic segmentation of retinal vessels simultaneously attaining grouping of arteries and veins; pg. 3, col. 2, para. 2) is configured to segment an artery and vein (achieved semantic classification of vessels to arteries and veins by assigning each pixel of retinal image a class label e.g., arteriole, venule, or background pixel; pg. 3, col. 2, para. 2) in a fundus image (retinal image; pg. 3, col. 2, para. 2; retinal fundus images for AV classification; pg. 6, col. 2, para. 2) to directly acquire an arteriovenous segmentation result (deep learning result comprising AV classification dataset; pg. 3, col. 2, para. 3), wherein the arteriovenous segmentation results (deep learning result comprising AV classification dataset; pg. 3, col. 2, para. 3) comprise an artery segmentation result and a vein segmentation result (AV classification dataset comprising achieved semantic classification of vessels to arteries and veins; pg. 3, col. 2, para. 2-3), and an arteriovenous vessel annotation result (class label e.g., arteriole and venule, gold standard labels of AV classification and vessel
segmentation; pg. 3, col. 2, para. 2-3) of a training fundus image (optimized deep CNN trained and evaluated on large newly prepared AV classification dataset of 700 retinal images that helped optimize the learned model and its results; pg. 3, col. 2, para. 3), the arteriovenous vessel annotation results comprising an artery annotation result and a vein annotation result (class label e.g., arteriole and venule, gold standard labels of AV classification and vessel segmentation; pg. 3, col. 2, para. 2-3) formed by annotating a boundary of a vessel with a vessel diameter greater than a pre-set vessel diameter (pixel-to-pixel similarity
measure, achieved by comparing pixel from segmented image to same pixel in ground truth and building matrix and performing calculation of desired performance measures; pg. 5, col. 1, para, 2-3) in the training fundus image (optimized deep CNN trained and evaluated on large newly prepared AV classification dataset of 700 retinal images that helped optimize the learned model and its results; pg. 3, col. 2, para. 3) and a small vessel annotation result formed by annotating a direction of a vessel not greater than the pre-set vessel diameter (thin vessels in labelled image defined as vessels that are less than four-pixel width, pixel-to-pixel similarity measure, achieved by comparing pixel from segmented image to same pixel in ground truth and building matrix and performing calculation of desired performance measures; pg. 5, col. 1, para, 2-3), when a loss function is calculated (pixel-wise loss calculation; pg. 5, col. 1, para, 2-3), a weight of a region corresponding to the small vessel annotation result is adjusted based on the small vessel annotation result (thin vessels in labelled image defined as vessels that are less than four-pixel width; pg. 5, col. 1, para, 2-3; adding segment-wise contextual judgment to loss function that optimizes vessel classification, applying optimized deep learning method on newly prepared AV classification dataset, improving accuracy of labels annotated as thin vessels, i.e., deep learning-based pixel level semantic segmentation utilized in classifying retinal blood vessels into arterioles/venules; pg. 2, col. 1, para. 4).
Therefore, it would have been obvious to a person having ordinary skill in the art, before the effective filing date of the claimed invention, to modify the method for determining the diameter of arteries and veins in a fundus image of Jin to further specify the technical features of weighted multi-task segmentation of retinal vessels through a multiloss function optimized deep encoder-decoder/CNN based design for classifying retinal image pixels into arterioles and venules, for the purpose of targeting better optimization of vessel classification, increasing accurate results, reducing bias in sensitivity, fixing artery segment pixels that are wrongly judged as vein pixels, and fixing vein pixels that are judged as arteries in deep learning, as taught by Badawi (pg. 3, col. 2, para. 2-3 and pg. 5, col. 1, para. 4).
Furthermore, and under the principles of inherency, if a prior art device, in its normal and usual operation, would necessarily perform the method claimed, then the method claimed will be considered to be anticipated by the prior art device. When the prior art device is the same as a device described in the specification for carrying out the claimed method, it can be assumed the device will inherently perform the claimed process. In re King, 801 F.2d 1324, 231 USPQ 136 (Fed. Cir. 1986). See MPEP § 2112.02.
With respect to Claim 14, Jin in view of Badawi teaches the measuring method (method for determining the diameter of arteries and veins in a fundus image; [0045]; Jin) according to claim 13, wherein:
the first region (center of the position of the optic disc; [0064]) is a region of a first circle formed by taking a circle center of a circumscribed circle of the optic disc region as the center ([0064]) and a first pre-set multiple (v1) of a diameter of the circumscribed circle as the diameter (optic disc is represented by the positions of multiple points representing the contour of the shape and size of the optic disc; [0064]; Jin);
the second region (first distance; [0064]) is a region from an edge of the first region (center of the position of the optic disc; [0064]) to a second circle formed by taking the circle center as the center (distance between the inner circle of the annular area and the optic disc; [0064]) and a second pre-set multiple (v2) of the diameter of the circumscribed circle as the diameter (optic disc is represented by the positions of multiple points representing the contour of the shape and size of the optic disc; [0064]; Jin);
the third region (second distance; [0064]) is a region from an edge of the second region (first distance; [0064]) to a third circle formed by taking the circle center as the center (distance between the outer circle of the annular area and the optic disc; [0064]) and a third pre-set multiple (v3) of the diameter of the circumscribed circle (optic disc is represented by the positions of multiple points representing the contour of the shape and size of the optic disc; [0064]; Jin); and
v1 < v2 < v3 ([0064]; Jin).
With respect to Claim 15, Jin in view of Badawi teaches the measuring method (method for determining the diameter of arteries and veins in a fundus image; [0045]; Jin) according to claim 14, wherein:
if the arteriovenous cross-indentation features are measured (crossed blood vessels; [0014]), the arteriovenous segmentation results of a fundus region except the first region (center of the position of the optic disc; [0064]) and the second region (first distance; [0064]) are thinned to acquire a first vessel skeleton comprising a plurality of skeleton pixel points taken as first measurement pixel points and to acquire a number of skeleton pixel points within a pre-set range of each of the first measurement pixel points as a first adjacent point number ([0014]; Jin);
pixel points in the arteriovenous segmentation results correspond to the first measurement pixel points of which the number of first adjacent points is greater than a first pre-set number are taken as arteriovenous cross positions ([0014]; Jin);
arteriovenous cross-indentation features are measured based on a ratio of proximal and distal vessel diameters in the arteriovenous segmentation results along the direction of extension of the vein segmentation result and on each of both sides of the arteriovenous cross position ([0014]; Jin); and
the first pre-set number is 3 ([0014]; Jin).
The broadest reasonable interpretation of a method (or process) claim having contingent limitations requires only those steps that must be performed and does not include steps that are not required to be performed because the condition(s) precedent are not met, and thus, “if the arteriovenous cross-indentation features are measured” is not a required step and is merely an optional limitation since the condition(s) precedent is not met. See MPEP § 2111.04 (II).
With respect to Claim 16, Jin in view of Badawi teaches the measuring method (method for determining the diameter of arteries and veins in a fundus image; [0045]; Jin) according to claim 15, wherein:
if the vein segmentation result is discontinuous at the arteriovenous cross position (crossed blood vessels; [0014]) in the arteriovenous segmentation result, a proximal end of each side is a skeleton pixel point on the first vessel skeleton of the vein segmentation result which is closest to the arteriovenous cross position ([0014]; Jin);
if the vein segmentation result is continuous at the arteriovenous cross position in the arteriovenous segmentation result, the proximal end of each side is the arteriovenous cross position ([0014]; Jin);
a distal end of each side is a skeleton pixel point on the first vessel skeleton of the vein segmentation result to which a distance from the arteriovenous cross position is a first pre-set distance ([0014]; Jin); and
the first pre-set distance is 2 to 4 times of a maximum vessel diameter ([0014]; Jin).
The broadest reasonable interpretation of a method (or process) claim having contingent limitations requires only those steps that must be performed and does not include steps that are not required to be performed because the condition(s) precedent are not met, and thus, “if the vein segmentation result is discontinuous/continuous” is not a required step and is merely an optional limitation since the condition(s) precedent is not met. See MPEP § 2111.04 (II).
With respect to Claim 17, Jin in view of Badawi teaches the measuring method (method for determining the diameter of arteries and veins in a fundus image; [0045]; Jin) according to claim 14, wherein:
if the arteriolar local stenosis features are measured (narrowing the recognition range, which not only reduces the computational complexity but also increases the accuracy; [0010]), the artery segmentation result is thinned to acquire a second vessel skeleton comprising a plurality of skeleton pixel points taken as second measurement pixel points ([0010]; Jin);
a number of skeleton pixel points within a pre-set range of each of the second measurement pixel points are acquired as a second adjacent point number, the second measurement pixel points with the number of second adjacent points being greater than the second pre-set number are deleted to obtain a plurality of vessel segments ([0010]; Jin); and
the arteriolar local stenosis features are measured based on a ratio of a minimum vessel diameter to a maximum vessel diameter of each vessel segment ([0010]; Jin).
The broadest reasonable interpretation of a method (or process) claim having contingent limitations requires only those steps that must be performed and does not include steps that are not required to be performed because the condition(s) precedent are not met, and thus, “if the arteriolar local stenosis features are measured” is not a required step and is merely an optional limitation since the condition(s) precedent is not met. See MPEP § 2111.04 (II).
With respect to Claim 18, Jin in view of Badawi teaches the measuring method (method for determining the diameter of arteries and veins in a fundus image; [0045]; Jin) according to claim 17, wherein:
the second pre-set number is 2 ([0010]; Jin);
v1 is 1, v2 is 2, and v3 is 3 ([0010]; Jin); and
the pre-set vessel diameter is 50 μm ([0010]; Jin).
The broadest reasonable interpretation of a method (or process) claim having contingent limitations requires only those steps that must be performed and does not include steps that are not required to be performed because the condition(s) precedent are not met, and thus, “if the arteriolar local stenosis features are measured… wherein: the second pre-set number is 2 ([0010]); v1 is 1, v2 is 2, and v3 is 3 ([0010]); and the pre-set vessel diameter is 50 μm” is not a required step and is merely an optional limitation since the condition(s) precedent is not met. See MPEP § 2111.04 (II).
With respect to Claim 19, Jin in view of Badawi teaches the measuring method (method for determining the diameter of arteries and veins in a fundus image; [0045]; Jin) according to claim 13, wherein the arteriovenous segmentation result is a three-value image (blood vessel segmentation image of the fundus image; [0055], a multi-value image comprising arteries, veins, and background; [0012] & [0053]; Jin).
With respect to Claim 20, Jin in view of Badawi teaches the measuring method (method for determining the diameter of arteries and veins in a fundus image; [0045]; Jin) according to claim 13, wherein the measurement is performed using the vessels with the diameter larger than the pre-set vessel diameter in the arteriovenous segmentation result (the larger the cosine value of the second angle between the two blood vessels in the blood vessel…[0018]; Jin).
With respect to Claim 21, Jin in view of Badawi teaches the measuring method (method for determining the diameter of arteries and veins in a fundus image; [0045]; Jin) according to claim 13, wherein the direction is used to estimate a region corresponding to a vessel not greater than the pre-set vessel diameter ([0018]) and the region is a curve that follows the direction of the vessel not greater than the pre-set vessel diameter (cosine value creating a curve; [0016-18]; Jin).
With respect to Claim 22, Jin in view of Badawi teaches the measuring method (method for determining the diameter of arteries and veins in a fundus image; [0045]; Jin) according to claim 13, wherein:
measuring a vessel diameter comprises performing resolution enhancement on the arteriovenous segmentation result according to a pre-set multiple to generate an enhanced arteriovenous segmentation result ([0099-100]; Jin);
extracting a vessel skeleton in the enhanced arteriovenous segmentation result and fitting the vessel skeleton to obtain a vessel diameter measurement direction of a continuous vessel skeleton and third measurement pixel points, the third measurement pixel points being a plurality of pixel points on the continuous vessel skeleton, and the vessel diameter measurement direction being perpendicular to a tangent line of the continuous vessel skeleton at the third measurement pixel points ([0099-100]; Jin);
using an interpolation algorithm to generate a vessel contour corresponding to the third measurement pixel points based on the enhanced arteriovenous segmentation result, the third measurement pixel points, the vessel diameter measurement direction of the third measurement pixel points, and a pre-set accuracy ([0099-100]; Jin);
calculating a vessel diameter corresponding to the third measurement pixel points based on a number of vessel pixel points in the vessel contour corresponding to the third measurement pixel points, the pre-set multiple, and the pre-set accuracy ([0099-100]; Jin); and
a vessel diameter l corresponding to the third measurement pixel points satisfies: l=n×s⁄e ([0099-100]; Jin);
wherein n is the number of vessel pixel points in the vessel contour corresponding to the third measurement pixel points, s is the pre-set accuracy, and e is the pre-set multiple ([0099-100]; Jin).
With respect to Claim 23, Jin in view of Badawi teaches the measuring method (method for determining the diameter of arteries and veins in a fundus image; [0045]; Jin) according to claim 13, wherein the weight is adjusted to zero (difference between the average values of the red component pixel values of the two blood vessels is less than or equal to 12, inclusive of weight being adjusted to zero; [0100]; Jin).
With respect to Claim 24, Jin in view of Badawi teaches the measuring method (method for determining the diameter of arteries and veins in a fundus image; [0045]; Jin) according to claim 13, wherein the arteriovenous segmentation result further comprises a background segmentation result (blood vessel segmentation image of the fundus image, as shown in fig. 2, wherein the white part in fig. 2 represents the blood vessel and the black part is the background; [0053]; Jin).
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to K MUHAMMAD whose telephone number is (571)272-4210. The examiner can normally be reached Monday - Thursday 1:00pm - 9:30pm EDT.
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/K MUHAMMAD/Examiner, Art Unit 2872 24 January 2026
/SHARRIEF I BROOME/Primary Examiner, Art Unit 2872